Revenue Automation Series: Building Revenue Data Pipeline Yizheng Zhang, Software Engineer; Yirun Zhou, Software Engineer Feb 19, 2025 Background As Yelp’s business continues to grow, the revenue streams have become...

Yelp's platform is a central hub for consumers and businesses, offering insights into local businesses, user reviews, and recommendations. Through articles, guides, and user-generated content, Yelp offers insights into discovering restaurants, shops, and services in various locations. Readers can learn about reading and writing reviews, finding popular businesses, and exploring local communities to make informed decisions about where to eat, shop, or visit.

Yelp Engineering

Yelp faced challenges in automating their revenue recognition process due to the complexity of revenue streams and manual operations. They developed a data pipeline using a Revenue Recognition SaaS solution (REVREC), integrating Yelp’s data with a standardized ETL architecture. The process included handling ambiguous requirements, performing data gap analysis, and evaluating system designs. Ultimately, Yelp chose a Data Lake + Spark ETL approach and utilized internal tools to manage the ETL pipeline, address technical challenges, and streamline debugging. Future improvements include enhanced data interfaces, simplified data models, and unified implementation standards.

Revenue Automation Series: Building Revenue Data Pipeline

Our Journey to Automated Revenue Recognition